Publications by authors named "Werickson Fortunato de Carvalho Rocha"

Requirements for blends of drop-in petroleum/bio-derived fuels with specific thermophysical and thermochemical properties highlights the need for chemometric models that can predict these properties. Multivariate calibration methods were evaluated using the measured thermograms (i.e.

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The lack of stringent regulations regarding raw materials for herbal supplements used for medicinal purposes has been a constant challenge in the industry. Ginkgo biloba L. leaf extracts attract consumers because of the supposed positive effect on mental performance and memory.

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Food analysis is a challenging analytical problem, often addressed using sophisticated laboratory methods that produce large data sets. Linear and non-linear multivariate methods can be used to process these types of datasets and to answer questions such as whether product origin is accurately labeled or whether a product is safe to eat. In this review, we present the application of non-linear methods such as artificial neural networks, support vector machines, self-organizing maps, and multi-layer artificial neural networks in the field of chemometrics related to food analysis.

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The physicochemical properties of a substance, such as a fuel, can vary significantly with composition. Determining these properties with ASTM standard methods is both expensive and time-consuming, which has led to a desire to use chemometric modeling as an alternative. In this study, we compare the accuracy and robustness of two chemometric models, partial least squares (PLS) regression and support vector machine (SVM) with uncertainty estimation to determine how the physicochemical properties depend on the composition.

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Recent progress in metabolomics has been aided by the development of analysis techniques such as gas and liquid chromatography coupled with mass spectrometry (GC-MS and LC-MS) and nuclear magnetic resonance (NMR) spectroscopy. The vast quantities of data produced by these techniques has resulted in an increase in the use of machine algorithms that can aid in the interpretation of this data, such as principal components analysis (PCA) and partial least squares (PLS). Techniques such as these can be applied to biomarker discovery, interlaboratory comparison, and clinical diagnoses.

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Process quality control and reproducibility in emerging measurement fields such as metabolomics is normally assured by interlaboratory comparison testing. As a part of this testing process, spectral features from a spectroscopic method such as nuclear magnetic resonance (NMR) spectroscopy are attributed to particular analytes within a mixture, and it is the metabolite concentrations that are returned for comparison between laboratories. However, data quality may also be assessed directly by using binned spectral data before the time-consuming identification and quantification.

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As feedstocks transition from conventional oil to unconventional petroleum sources and biomass, it will be necessary to determine whether a particular fuel or fuel blend is suitable for use in engines. Certifying a fuel as safe for use is time-consuming and expensive and must be performed for each new fuel. In principle, suitability of a fuel should be completely determined by its chemical composition.

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We describe the identification and limits of detection of ink staining by mass spectrometry imaging (MSI), as used in anti-theft devices (ATDs). Such ink staining is applied to banknotes during automated teller machine (ATM) explosions. Desorption electrospray ionization (DESI) coupled with high-resolution and high-accuracy orbitrap mass spectrometry (MS) and a moving stage device were applied to obtain 2D molecular images of the major dyes used for staining, that is, 1-methylaminoanthraquinone (MAAQ), rhodamine B (RB) and rhodamine 6G (R6G).

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Using Brazilian banknotes as a test case, forensic examination and identification of Rhodamine B dye anti-theft device (ATD) staining on banknotes were performed. Easy ambient sonic spray ionization mass spectrometry (EASI-MS) was used since it allows fast and simple analysis with no sample preparation providing molecular screening of the surface with direct desorption and ionization of the security dye. For a more accurate molecular characterization of the ATD dye, Q Exactive Orbitrap™ Fourier transform (tandem) mass spectrometry using eletrospray ionization (ESI-HRMS/MS) was also applied.

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Article Synopsis
  • ANFO (Ammonium Nitrate Fuel Oil) is commonly used for civil purposes but has been misused in criminal acts like ATM explosions in Brazil.
  • This study utilizes advanced mass spectrometry techniques, including FT-ICR and EASI-MS, to analyze ANFO and identify its main components (diesel and nitrate explosive) and an ion marker specifically for ANFO.
  • The research demonstrates the successful detection of the ANFO ion marker on banknotes that were at crime scenes, showcasing a method to link explosives to criminal activities.
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Using a desorption/ionization technique, easy ambient sonic-spray ionization coupled to mass spectrometry (EASI-MS), documents related to the 2nd generation of Brazilian Real currency (R$) were screened in the positive ion mode for authenticity based on chemical profiles obtained directly from the banknote surface. Characteristic profiles were observed for authentic, seized suspect counterfeit and counterfeited homemade banknotes from inkjet and laserjet printers. The chemicals in the authentic banknotes' surface were detected via a few minor sets of ions, namely from the plasticizers bis(2-ethylhexyl)phthalate (DEHP) and dibutyl phthalate (DBP), most likely related to the official offset printing process, and other common quaternary ammonium cations, presenting a similar chemical profile to 1st-generation R$.

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Raman spectroscopy and control charts based on the net analyte signal (NAS) were applied to polymorphic characterization of carbamazepine. Carbamazepine presents four polymorphic forms: I-IV (dihydrate). X-ray powder diffraction was used as a reference technique.

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